# Models and algorithms for the next generation of glass transition studies

## TL;DR

This paper introduces optimized models of polydisperse supercooled liquids and an efficient swap Monte Carlo algorithm, enabling rapid equilibration and advancing computational studies of glass-forming materials.

## Contribution

It develops novel glass-forming models with enhanced stability and efficiency through combined optimization of particle properties and swap algorithms.

## Key findings

- Achieved over ten orders of magnitude acceleration in equilibration times
- Identified key factors like softness and polydispersity for model robustness
- Provided microscopic insights into swap algorithm performance

## Abstract

Successful computer studies of glass-forming materials need to overcome both the natural tendency to structural ordering and the dramatic increase of relaxation times at low temperatures. We present a comprehensive analysis of eleven glass-forming models to demonstrate that both challenges can be efficiently tackled using carefully designed models of size polydisperse supercooled liquids together with an efficient Monte Carlo algorithm where translational particle displacements are complemented by swaps of particle pairs. We study a broad range of size polydispersities, using both discrete and continuous mixtures, and we systematically investigate the role of particle softness, attractivity and non-additivity of the interactions. Each system is characterized by its robustness against structural ordering and by the efficiency of the swap Monte Carlo algorithm. We show that the combined optimisation of the potential's softness, polydispersity and non-additivity leads to novel computer models with excellent glass-forming ability. For such models, we achieve over ten orders of magnitude gain in the equilibration timescale using the swap Monte Carlo algorithm, thus paving the way to computational studies of static and thermodynamic properties under experimental conditions. In addition, we provide microscopic insights into the performance of the swap algorithm which should help optimizing models and algorithms even further.